This study conducts a dynamic rolling comparison between the Pareto/NBD model (parametric model) and machine learning algorithms (observation-driven models) in customer base analysis, which the literature has not comprehensively investigated before. The aim is to find the comparative edge of...

This study conducts a dynamic rolling comparison between the Pareto/NBD model (parametric model) and machine learning algorithms (observation-driven models) in customer base analysis, which the literature has not comprehensively investigated before. The aim is to find the comparative edge of...

This paper compares various models for time series of counts which can account for discreetness, overdispersion and serial correlation. Besides observation- and parameter-driven models based upon corresponding conditional Poisson distributions, we also consider a dynamic ordered probit model as...

This paper compares various models for time series of counts which can account for discreetness, overdispersion and serial correlation. Besides observation- and parameter-driven models based upon corresponding conditional Poisson distributions, we also consider a dynamic ordered probit model as...